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Multi objective optimization of solid oxide fuel cell stacks considering parameter effects: Fuel utilization and hydrogen cost

Behzadi Forough, A ; Sharif University of Technology | 2013

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  1. Type of Document: Article
  2. DOI: 10.1063/1.4822253
  3. Publisher: 2013
  4. Abstract:
  5. In the context of stationary power generation, fuel cell based systems are being predicted as a valuable option to tabernacle the thermodynamic cycle based power plants. In this paper, multi objective optimization approach is used to optimize the planer solid oxide fuel cell (SOFC) stacks performance using genetic algorithm technique. Multi objective optimization generates the most attractive operating conditions of a SOFC system. This allows performing the optimization of the system regarding to two different objectives. Two pairs of different objectives are considered in this paper as distinguished strategies. In the first strategy, minimization of the breakeven per-unit energy cost ($/kWh) and maximization of the output power is considered. Similarly, two other objectives are also considered in the second strategy as minimization of the breakeven per-unit energy cost ($/kWh) and maximization of the electrical efficiency. Optimization of the first strategy predicts a maximum power output of 108.33 kW at a breakeven per-unit energy cost of 0.51 $/kWh and minimum breakeven per-unit energy cost of 0.30 $/kWh at a power of 42.18 kW. In the second strategy, maximum efficiency of 63.93% at a breakeven per-unit energy cost of 0.42$/kWh is predicted, while minimum breakeven per-unit energy cost of 0.25 $/kWh at efficiency of 48.3% is obtained. At the end, evaluation of parameter effects on multi objective optimization regarding different hydrogen costs and fuel utilization factors are presented. It is worthy to note that the sensitivity analysis for multi objective optimization can be considered both as an advanced analysis tool and as support to technology managers, engineers, and decision makers when working by such as systems
  6. Keywords:
  7. Electrical efficiency ; Evaluation of parameters ; Maximum power output ; Operating condition ; Solid oxide fuel cell stack ; Stationary power generation ; Technology managers ; Thermodynamic cycle ; Costs ; Energy efficiency ; Genetic algorithms ; Solid oxide fuel cells (SOFC) ; Thermodynamic properties ; Optimization
  8. Source: Journal of Renewable and Sustainable Energy ; Volume 5, Issue 5 , 2013 ; 19417012 (ISSN)
  9. URL: http://scitation.aip.org/content/aip/journal/jrse/5/5/10.1063/1.4822253